CRM and Personalization: Email Tech Is Now Ad Tech

email symbol on row of colourful envelopeseBay has come a long way in our CRM and email marketing in the past two years. Personalization is a relatively easy task when you’re dealing with just one region and one vertical and a hundred thousand customers. With 167M active buyers across the globe, eBay’s journey to help each of our buyers find their version of perfect was quite complex.

Like many in our industry, we’ve had to deal with legacy systems, scalability, and engineering resource constraints. And yet, we’ve made email marketing a point of pride — instead of the “check mark” that we started from. Here’s our story.

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May the Odds Be Ever in Your Favor

aaeaaqaaaaaaaapzaaaajgnkyzcznta1ltfjn2itnge0os1iodhmltljzgq3ywexotq4mqIn life as in work, we’re constantly dealing with uncertainty. As parents, employees, leaders, we look at the future and estimate the odds: what’s the chance that our teenage son will do drugs? What’s the chance that this system’s load will exceed what we designed it for? How likely is this risky investment to result in a huge competitive advantage?

We estimate these chances, and some of us are better than others; we look at the data, ask for advice, look for prior examples. We are hard-wired to estimate the chances – and to over-value potential loss over potential gain, and over-value action over allowing things to proceed on their own. The best of us identify their built-in biases and adjust their decision-making accordingly, but even they can’t avoid the “sacred geometry of chance.“ Continue reading

If your team isn’t on-track, try this

bored-teamThe most concise, truly beautiful definition of leadership I’ve heard is “having others WANT to follow you.” This definition means two things 1) that you’re actually moving somewhere, not standing still and 2) that others are convinced, not coerced, into going along.

There are so many leadership books out there, some talking about vision, some about audacity, some about authenticity. Advice is often mysterious and convoluted — we hear of “executive maturity” (perfectly ambiguous excuse to keep the outsiders away) and of “situational leadership” (sorry, there are no best practices … every situation is different). Continue reading

Your team just screwed up badly — here’s what you do next

disasterYou’ve been there. Someone on your team just screwed it up. Your production website went down in the middle of the night, it took hours to bring it back up. It’s 10am the next day, you’re at your daily standup, and the culprit is looking down, ashamed and quiet; the team is noticeably uncomfortable and is expecting you, their leader, to scream and shout about business impact and accountability and how bad this all is.

You’re upset. The outage already cost your group some reputation — you’re seeing tweets and a message from the investor, and you have no idea how something this dumb could have been overlooked.

You can allow your emotions to take over. You can do the screaming, you can shame the perpetrator, who will undoubtedly remember this occasion and probably won’t make a mistake of this kind again. You will scare others at the standup enough for them to be afraid of their own shadow for the next week.

Or you can take a breath.

And ask yourself. Continue reading

Machine Learning and Digital Marketing: Melding Human and Machine

In digital, you can easily spot two opposing camps — the artists and the quants.

Artists are folks like the New York Times: Pulitzer prize-winning journalists use their intuition and skill — their unique talents — to create one-of-a-kind stories, and the judgment of the Chief Editor is pure gold. Artists create incredible brand value; true loyalty — lifelong fans.

human-man-and-machineshutterstock_250853188-620x615Quants are folks like eHow.com. They use Wall Street-style algorithms to identify long-tail Google queries that have weak competition, and pay amateur writers $5 to create short posts that address those queries. Queries like “how to remove gum from clothing.” Their quant models tell them that stories like this will make $7 on ads in the next year, so they pump out millions of such stories.

Both approaches have problems. If a New York Times writer gets hit by a bus, there’s no replacing them. Their talent dependency is not scalable. eHow stories — millions of them — inspire no loyalty, create no brand value. Let’s face it, it’s crappy content. No wonder Google did everything in its power to kill it. Continue reading